Data Scientist

McCormick & Company•HUNT VALLEY, MD

23h•Onsite

About The Position

McCormick & Company, Inc. is seeking a Data Scientist to create advanced analytical models and solutions that provide real-time insights for decision-makers, focusing on ROI and business impact. This role involves enhancing data collection, processing and verifying data for integrity, and developing end-to-end data validation scripts using Python for large-scale data migrations between SQL and NoSQL environments. The Data Scientist will translate data and analytics into business insights using Machine Learning, Python, SQL, and Azure ML to optimize manufacturing, supply chain, and product innovation. A key responsibility includes designing and deploying LLM-powered web interface bots for manufacturing environments, allowing non-technical users to interact with complex operational data and automated workflows through conversational interfaces. The role also drives the development of scalable data pipelines and machine learning workflows using cloud platforms like Azure (DevOps, ML, ADLS Gen2), builds and optimizes Spark ETL applications, and builds and deploys predictive scoring models. Additionally, the Data Scientist will perform statistical modeling, develop and deploy machine learning models on HR datasets (including sentiment analysis of employee survey responses and predictive modeling for retention risk), and automate business processes. The position requires researching industry best practices to develop new data analytics capabilities and drive digitalization strategy, business process enhancements, and automations. Collaboration with cross-functional teams (procurement, R&D, production) to align data-driven strategies with business goals is essential, as is serving as a liaison between technical and non-technical stakeholders.

Requirements

Master’s degree in Data Analytics/Science, Computer Science or related field
24 months of experience in the job offered or related occupation
2 years’ experience developing and executing end-to-end data validation scripts using Python for large-scale data migrations between database environments including SQL and NoSQL environments.
2 years’ experience with PowerBI and Tableau data visualization software.
2 years’ experience developing predictive models.
2 years’ experience building and optimizing Spark ETL applications.
2 years’ experience designing and deploying scalable data ingestion and processing pipelines on cloud infrastructure using Azure, AWS or Google.
2 years’ experience using MLflow experiment tracking and model lifecycle management tools for logging, versioning, and deploying machine learning models in cloud environments.
1 year experience with SAP ERP system, specifically, APO and SAP S/4HANA supply chain modules.

Responsibilities

Create advanced analytical models and solutions to provide real-time insights for decision-makers focusing on ROI and business impact using Python, Tableau and PowerBI.
Enhance data collection procedures.
Process and verify data to ensure integrity.
Develop and execute end-to-end data validation scripts using Python for large-scale data migrations between database environments including SQL and NoSQL environments.
Translate data and analytics into business insights using Machine Learning, Python, SQL and Azure ML to optimize manufacturing, supply chain, and product innovation.
Design and deploy LLM-powered web interface bots for manufacturing environments, enabling non-technical users to interact with complex operational data and automated workflows through conversational interfaces.
Drive the development of scalable data pipelines and machine learning workflows using cloud-based platforms including Azure (DevOps, ML, ADLS Gen2).
Build and optimize Spark ETL applications.
Build and deploy predictive scoring models.
Complete statistical modeling.
Develop and deploy machine learning models on HR datasets, including sentiment analysis of employee survey responses and predictive modeling to identify retention risk and drive data-driven workforce strategy.
Automate business processes.
Research industry best practices and skills to develop new capabilities for data analytics for the Company and drive its digitalization strategy and business process enhancements and automations.
Collaborate with cross-functional teams, including procurement, R&D and production, to align data-driven strategies with business goals.
Serve as a liaison between technical and non-technical stakeholders, ensuring alignment and understanding.